Exploration and targeting of gold mineralisation in Burkina Faso using Airborne Geophysics

This presentation was recorded at PDAC 2020.

Overview

Video Transcript

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(gentle music)

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<v ->Good afternoon, everybody.</v>

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Welcome back to PDAC.

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My name is James Lawton.

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I’m the Chief Technology Officer for Seequent.

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Before we get into this afternoon’s presentation,

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just wanted to give a few words on what we’re doing

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in terms of future directions across Seequent.

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As you probably all know, or hopefully you know,

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Seequent has three broad portfolios:

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Geological, Geophysical, as well as Geo-technical.

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And across all of those portfolios,

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we’re deeply investing in each of them.

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Especially in the geo-physical,

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especially in the geological,

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and wait a minute,

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especially in the geo-technical as well.

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So everywhere.

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We’re also moving from just pure desktop software

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into a hybrid model,

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where you can run that software both on-premise,

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on a desktop, and in the cloud.

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And then moving towards pure cloud applications,

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which we already have today.

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As part of that overall movement or change

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and some of the focus,

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we’re also investing heavily in core building blocks.

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The first of those is already out there,

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Seequent ID,

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providing a universal ID

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that allows you to move seamlessly

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from one spot in that workflow.

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One piece of our portfolio to another,

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without having to sign in again,

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without having to worry

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about whether you’re going to get access

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to the data that you placed there.

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The other things that we’re working on

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are automatic ingesting of data,

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so that you don’t have to have manual intervention.

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You don’t have to worry

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about where the data is coming from.

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Bringing in to each of those elements.

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We’re also working on automatic model updates,

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so that when the data changes,

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you get automatic model changes.

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And that could be in Oasis motaj.

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It could be in Voxy,

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it could be in LeapFrog,

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it could be in GeoStudio.

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It could be in any single one of those.

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So we’re also continuing to add more innovation

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into the desktop products.

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Adding more science,

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more updates to the core algorithms,

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to the core pieces of features, of functions.

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We’re also investing heavily in performance.

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And so as the products all start rolling out

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in their next iteration in May,

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you’re going to see dramatic performance improvements

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across the board,

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especially in Oasis montaj

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and in LeapFrog.

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And brand new stuff coming in,

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in the GeoStudio arena as well.

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Beyond that, we’re looking deeply and heavily

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at data management overall.

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So not only we’d want to move your data through,

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what we also want to do is make sure it’s easy to find,

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easy to access,

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and again, just making it available,

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wherever, however, whenever you’re doing anything.

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Now, that’s enough for me.

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What I’m going to do is pass you over

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to our President presenter for today.

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So I’d like to welcome Jean Legault,

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the Chief Geophysicist at GeoTech.

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<v ->Thank you, thank you.</v>

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All right.
(audience applauding)

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Yeah, hi everyone.

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And it’s a pleasure to be here and thanks for coming.

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I’m going to be presenting a talk

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on the impact of geophysical surveys

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on exploration for gold mineralization, Burkina Faso.

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It’s actually, you can see there’s eight authors here

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and I’m the very last one,

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but I’ve presented it at,

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the main author Nasreddine Bournas couldn’t be here today,

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so I’m presenting it for you.

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I presented it at,

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we presented this paper at the SCG last year.

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So I recognize the co-authors,

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these are Toure, Balbone, Zagre, Ouedraogo

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they’re all with the government of Burkina Faso in Buja.

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and Kanita Khaled who’s now here at Seequent

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and Alexander Prikhodko,

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who was the previous User Data Processing manager

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and the chief geophys and I’m the last speaker.

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So here’s the outline of my talk,

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basically, what this is,

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it’s actually a showcase of a CET Lineament Analysis tool,

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offered on the GeoSoft platform.

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And it actually worked very, very well.

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We’re very impressed with the software.

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The whole paper is based on this.

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If I can give you a kind of like a bit of a backstory.

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We completed a large survey

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for the government of Burkina Faso.

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They have this beautiful dataset

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and they want to be able to promote this around the world.

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And they suggested, well,

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why don’t we try to write a paper

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on what are we going to do with such a massive dataset?

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Well, let’s try the CET analysis and see what comes of it.

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And this paper comes out of this.

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I think you’d be very surprised

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at how interesting the results were.

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So I’m going to give an overview of Lineament Analysis

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that is called LA.

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Or we will present the Burkinian geophysical data.

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And I’m going to show you the results

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of that Lineament Analysis before concluding.

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So obviously when you’ve got like large airborne datasets,

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like we’re involved in, we collect data around the world.

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This particular data set

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is probably almost a half a million

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where I collect data from over a period of decades.

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You’ve got to be able to interpret these large data sets,

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and they’re such large volumes and they’re very complicated.

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And how do you do that in just a limited amount of time?

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So there’s for us, our clients,

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aren’t satisfied with just getting the geophysical data.

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You better provide an adamant product.

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Something that will add a little spark to your dataset

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that will encourage explorers to invest in the country.

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And so one of the easiest ways,

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rather than toil over datasets for years on end

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is to use these sediments semi-automated tools

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and machine learning languages, algorithms, I should say.

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And really this is how we’ve dealt with the big data.

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And makes it faster, it’s more objective.

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That’s the big thing is how do you remain consistent

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in your approach to a dataset?

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These semi-automated tools allow you to do that.

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And so our clients are very pleased with that.

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They, they responded that they liked

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that aspect of the dataset.

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And these results from,

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the example I’m going to show you

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is just a gold exploration application,

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using these so-called heat maps.

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So Lineament Analysis goes like this,

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you’ve got these,

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we all know that these Epithermal/Mesothermal

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sheer hosted gold deposits are associated

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with a hundreds of thermal alteration,

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but they’re all structurally controlled.

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We all know this.

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And so the CET analysis is based on these premises.

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You do a texture analysis,

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then you do a ridge detection,

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thinning and vectorization.

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This is the basic steps.

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And then we organize these into what they call heat maps.

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And these are all to benefit, primarily, in this case,

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gold exploration and targeting.

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Like I said, these are all performed

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on the CET analysis tool on the Oasis montaj platform.

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Just very vaguely, I’m sure that Nasreddine

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would do a much better job at explaining all of these,

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but the Ridge detection is using log-Gabor wavelets.

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We also look at orientation,

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once you’ve got the Ridge detection,

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you can apply different features,

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to look for different aspects.

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You can look for intersections of density,

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but you can also look for orientation diversity.

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So those are the two steps

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based on these authors in their work.

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This is the geology and Burkina Faso.

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Primarily, through the middle of these purples,

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represent these Eburian Granitoids

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You’ve also got a Paleo-Proterozoic Basement

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in yellow and green and through the middle.

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On the west side, there’s Neo-Proterozoic Sedimentary Cover.

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On the east side, there’s also a Cenozoic Terrains.

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So the area in the middle is basically

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what we’re focusing on.

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This is where the gold mineralization is in Burkina Faso.

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These are the overview of the gold mineralization

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that is there.

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You can see there’s a number of deposits.

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It’s very important for gold.

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And, but there are other types of mineralization,

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zinc, copper.

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It’s a very rich country.

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But obviously it’s still a poor country.

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And so well, they’re trying as best as they can

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to promote exploration

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using these EU and world bank funded geophysical programs.

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This is before the 1990s, they didn’t,

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and that’s not atypical.

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There’s very little information,

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very few sparse surveys

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involving magnetics radiometrics and EM.

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But starting in 1998, 99, CGG

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formerly , produced the first part of the survey,

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most of it on the Eastern border,

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you can see there’s differences in resolution.

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That’s where the shield areas or the focused area

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and the sedimentary area has much smoother.

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You can see that there’s a distinctive difference

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between the two.

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One is flown at one kilometer spacings

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on the Western side,

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and the other side is flown with a 500 meter spacings.

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This is the block that we flew from 2015 to 2016,

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represents about it,

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I’m not sure how big the CGG block was,

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but our block was about 150,000 line kilometers.

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And we flew to that at 400 meters spacing

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with five kilometer ties.

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And then more recently, there is a Xcalibur completed.

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So this is actually a high resolution image

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of the magnetic map of Burkina Faso.

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We don’t get to see a lot of these datasets very often,

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but that’s what a full country coverage looks like

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in Burkina Faso.

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So now what?

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We’ve got this data, what do we do with it?

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Well, we know regionally

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they have these known geological structures

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that they’ve mapped along, which they find gold deposits

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that are shown in white.

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There there’s this,

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the Western shear zone has gold deposits

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and this eastern shear zone

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called the Timberly-Dory Marking sheer zone.

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Anyway, you can see that the gold deposits

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are aligned along both.

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And what did we do?

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We just like, very simply we used the CET analysis

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and came up with these lineaments.

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So this is, it’s basically, semi-automated.

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Here we have all the lineaments that are generated.

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Now, what would we do?

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Well, we just kind of like, just focus.

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How did we get all of those?

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This is very dense data.

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And basically I’m showing you,

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like an interpreter would have a hard time

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coming up with this.

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But it’s done semi-automatically, right?

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This is what’s called a,

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it’s an output of the CET program.

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It’s called the Lineament Intersection Density Map.

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So it’s showing you basically

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where the computer’s calculated the largest density

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of these lineaments.

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And you can see the correlation with the gold.

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There’s many of the gold deposits that are associated

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with these high density intersections,

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of course, but not all.

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I mean, there are exceptions.

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You can see there are exceptions

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where in the warm colors

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where the all gold deposits aren’t situated.

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This is a different look,

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that one was orientation density,

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now we’re looking at orientation diversity.

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So the diversity of lineaments

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that were calculated within that space.

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And now you actually see a much better correlation

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with the non gold zones,

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much better correlation.

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And this is using a radius of influence of 20 kilometers.

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So basically, looking at density,

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think of it as a, just an area of an area of interest,

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20 kilometers wide, how you generated these.

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20 kilometers there’s the bottom of the scale.

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It is on the bottom.

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This is a different map.

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If I kind of like, this is,

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that was 20 kilometer density radius of influence.

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This is five kilometers,

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so much more focused.

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And it’s actually surprising how much better you can see.

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There’s much more correlation.

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One thing that interested us too, though,

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just on the Southeast side,

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where you’ve got nicest density,

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and these are areas that point to greater potential

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in the Southeastern corner of the belt.

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So if we just focus in this was called the Golden Y.

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So the there’s kind of like a split in the structure.

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And you can see how almost all of these gold deposits lie

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within these influence.

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And this is semi-automated

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it’s like hours to perform on a dataset.

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Just, you know, we also collected radiometrics.

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So this is just a map of the radiometric image.

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It’s very, very rich.

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These countries are ideal for flying radiometrics,

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looking for alteration mapping and so forth.

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And that was basically my presentation.

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Just to conclude, like we just showed,

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we have a country wide map,

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how can we quickly go through that map efficiently?

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And with using the CET tool we found a method to do that.

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And this is, anybody can perform it.

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I mean, we obviously we played with it.

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We’ve we applied this to regional scale.

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We even applied this to grid scale surveys.

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It’s a very, very useful tool.

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And it’s a very economical tool,

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it’s not overly costly, it’s very, very simple.

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We we use it almost continuously.

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We’re very, very pleased with the results.

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And like I said, for the government of Burkina Faso,

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what they were interested in was,

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hey, listen, we’ve identified areas

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where we know there’s mineralization.

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We’ve got areas that have similar results

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that are under explored,

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these represent areas for exploration potential.

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That’s the end of my presentation.

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Thank you very much.

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(audience clapping)